INSIDE-HEART aims to address the challenging problems related to collection, processing and relevance of digital biomarkers in the field of supraventricular arrhythmias (SVAs).
From a scientific point of view, there have been many advancements in atrial disease patients’ care, however several issues remain to be solved in two main areas: 1) Diagnosis and prognosis of SVAs through digital biomarkers, 2) Risk assessment of life-threatening events in patients with SVAs.
Area 1 –Digital Biomarkers for SVAs Detection and Monitoring: the research focuses on developing new digital biomarkers to advance the detection and monitoring of SVAs. The primary objectives are to reduce the minimum detection time for SVAs from the current standard of two-minute windows to just one minute, and to improve detection rates, aiming for a 20% increase in effect size. To achieve these goals, advanced signal processing and AI have been used to identify robust digital biomarkers across a broad spectrum of arrhythmias, including Atrial Fibrillation (AF), Atrial Flutter (AFL), Supraventricular Tachycardia (SVT), and, to a lesser extent, non-sustained ventricular tachycardia (NSVT). These efforts target diverse populations (e.g. infants, youth, adults, elderly, and patients with comorbidities) and employ a variety of data collection modalities, such as smartphones, smartwatches, implantable devices, patches, and more. The work involves acquiring biosignals from innovative devices, identifying key digital biomarkers, and validating these markers for effective SVA monitoring in real-world scenarios.
Area 2 – Digital Biomarkers for Risk Assessment: the research focuses on the development of predictive tools for adverse cardiovascular outcomes in patients with supraventricular arrhythmias (SVAs). Its objective is to identify and validate robust digital biomarkers that enable accurate risk stratification and support clinical decision-making across heterogeneous patient groups. Multi-modal ECG data from Holter monitors, standard clinical ECGs, wearable devices, and intracardiac recordings have been analyzed, with applicability in both clinical and real-world settings. To achieve these goals, expertise in signal processing, machine learning and deep learning, computational modelling, clinical electrophysiology, and wearable sensing technologies will be integrated. The work involves the development of clinically interpretable, scalable, and deployable digital biomarkers to improve prognostic assessment for atrial fibrillation progression, heart failure, post-ablation recurrence, and stroke risk, contributing to more personalized and data-driven management of SVA patients.
INSIDE-HEART fosters an ongoing exchange between researchers, clinicians, and industry partners to deepen understanding of the challenges from multiple perspectives. This sustained multidisciplinary interaction is expected to have a significant long-term impact on the DCs’ careers, equipping them with the ability to communicate effectively across academic, clinical, and industrial environments.
Moreover, INSIDE-HEART places strong emphasis on integrity, transparency, and ethical conduct in research. The DCs have disseminated their work through scientific conferences, the project website, and blog posts, and the consortium has also taken part in public engagement activities across Europe. Overall, INSIDE-HEART has met all its objectives to date, with strong progress and continued success anticipated.
